A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends

被引:201
作者
Kuntoglu, Mustafa [1 ]
Aslan, Abdullah [2 ]
Pimenov, Danil Yurievich [3 ]
Usca, Usame Ali [4 ]
Salur, Emin [5 ]
Gupta, Munish Kumar [3 ,6 ]
Mikolajczyk, Tadeusz [7 ]
Giasin, Khaled [8 ]
Kaplonek, Wojciech [9 ]
Sharma, Shubham [10 ]
机构
[1] Selcuk Univ, Fac Technol, Dept Mech Engn, TR-42130 Selcuklu, Konya, Turkey
[2] Selcuk Univ, Fac Engn & Architecture, Dept Mech Engn, TR-42130 Aksehir, Konya, Turkey
[3] South Ural State Univ, Dept Automated Mech Engn, Lenin Prosp 76, Chelyabinsk 454080, Russia
[4] Bingol Univ, Fac Engn & Architecture, Dept Mech Engn, TR-12000 Bingol, Turkey
[5] Selcuk Univ, Dept Met & Mat Engn, TR-42130 Selcuklu, Konya, Turkey
[6] Shandong Univ, Sch Mech Engn, Key Lab High Efficiency & Clean Mech Manufacture, Minist Educ, Jinan 250100, Peoples R China
[7] UTP Univ Sci & Technol, Dept Prod Engn, Al Prof S Kaliskiego 7, PL-85796 Bydgoszcz, Poland
[8] Univ Portsmouth, Sch Mech & Design Engn, Portsmouth PO1 3DJ, Hants, England
[9] Koszalin Univ Technol, Dept Prod Engn, Fac Mech Engn, Raclawicka 15-17, PL-75620 Koszalin, Poland
[10] IKG Punjab Tech Univ, Dept Mech Engn, Jalandhar Kapurthala Rd, Kapurthala 144603, Punjab, India
关键词
indirect tool condition monitoring systems; turning; machining; vibration; cutting force; acoustic emission; temperature; current; industry; 4.0; RESPONSE-SURFACE METHODOLOGY; ARTIFICIAL NEURAL-NETWORKS; ACOUSTIC-EMISSION SIGNALS; SUPPORT VECTOR MACHINE; CUTTING FORCE SIGNALS; AISI; 4140; STEEL; FLANK WEAR; STATISTICAL-ANALYSIS; COATING THICKNESS; EDGE-GEOMETRY;
D O I
10.3390/s21010108
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The complex structure of turning aggravates obtaining the desired results in terms of tool wear and surface roughness. The existence of high temperature and pressure make difficult to reach and observe the cutting area. In-direct tool condition, monitoring systems provide tracking the condition of cutting tool via several released or converted energy types, namely, heat, acoustic emission, vibration, cutting forces and motor current. Tool wear inevitably progresses during metal cutting and has a relationship with these energy types. Indirect tool condition monitoring systems use sensors situated around the cutting area to state the wear condition of the cutting tool without intervention to cutting zone. In this study, sensors mostly used in indirect tool condition monitoring systems and their correlations between tool wear are reviewed to summarize the literature survey in this field for the last two decades. The reviews about tool condition monitoring systems in turning are very limited, and relationship between measured variables such as tool wear and vibration require a detailed analysis. In this work, the main aim is to discuss the effect of sensorial data on tool wear by considering previous published papers. As a computer aided electronic and mechanical support system, tool condition monitoring paves the way for machining industry and the future and development of Industry 4.0.
引用
收藏
页码:1 / 33
页数:32
相关论文
共 170 条
[51]   Study of tool life, surface roughness and vibration in machining nodular cast iron with ceramic tool [J].
Ghani, AK ;
Choudhury, IA ;
Husni .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2002, 127 (01) :17-22
[52]   LEARNING AND EXTRACTING FINITE STATE AUTOMATA WITH 2ND-ORDER RECURRENT NEURAL NETWORKS [J].
GILES, CL ;
MILLER, CB ;
CHEN, D ;
CHEN, HH ;
SUN, GZ ;
LEE, YC .
NEURAL COMPUTATION, 1992, 4 (03) :393-405
[53]  
Groover M., 2019, FUNDAMENTALS MODERN
[54]   Predictive modeling of surface roughness in grinding [J].
Hecker, RL ;
Liang, SY .
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2003, 43 (08) :755-761
[55]   Cutting temperatures during hard turning-Measurements and effects on white layer formation in AISI 52100 [J].
Hosseini, S. B. ;
Beno, T. ;
Klement, U. ;
Kaminski, J. ;
Ryttberg, K. .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2014, 214 (06) :1293-1300
[56]   Application of AE and cutting force signals in tool condition monitoring in micro-milling [J].
Jemielniak, K. ;
Arrazola, P. J. .
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY, 2008, 1 (02) :97-102
[58]   Tool failure detection based on analysis of acoustic emission signals [J].
Jemielniak, K ;
Otman, O .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 1998, 76 (1-3) :192-197
[59]  
Jiang C.Y., 1987, Annals of the CIRP, V36, P45, DOI DOI 10.1016/S0007-8506(07)62550-5
[60]   Relevance of Roughness Parameters of Surface Finish in Precision Hard Turning [J].
Jouini, Nabil ;
Revel, Philippe ;
Bigerelle, Maxence .
SCANNING, 2014, 36 (01) :86-94